Thanks to research and modern healthcare the treatment of children and young with cancer become a success story. The overall five-year survival rate for children with cancer is about 85%. Unfortunately, in later life, complications associated with the cancer usually develop, and as many as 80% of survivors suffer from various long-term complications that are sometimes serious or life-threatening. After relapse or secondary malignancy, cardiovascular diseases) are the leading cause of morbidity and mortality among survivors.
Computational cardio-oncology is an exciting and rapidly evolving field that has the potential to improve the care of cancer patients who may be at risk for cardiovascular complications due to their cancer. By leveraging computational methods such as machine learning and big data statistics, researchers and clinicians can better understand the complex interactions between cancer and cardiovascular health, develop predictive models for cardiovascular risk, and identify new strategies for detecting cardiovascular complications in cancer patients.
Between 1958 and 2021, 65,173 patients < 25 years were identified in the National Cancer Register. We analyze data on patient- and socio-demographics, tumor characteristics, treatment modalities, and comorbidities compared with 313,108 controls without cancer with the same place of residence, age, and sex to identify potential predictors of cancer treatment-related cardiovascular toxicity (CTR-CVT). To identify risk factors of CTR-CVT, the above cohorts were linked to the National Patient Register and the Prescribed Drug Register. Additionally, the cohort was linked to the Cause of Death Registry to identify the date and cause of death and Swedish Social Insurance Agency and Statistics Sweden (SCB) to examine the sociodemographic impacts. All cohorts were matched with the SwedeHeart Registry, and several other organ specific national quality registers.
Ultimately, the success of computational cardio-oncology will depend on its ability to integrate with traditional clinical approaches and to produce actionable insights that can be translated into improved patient care. Therefore, it is likely that a combination of computational and clinical approaches will be needed to fully realize the potential of cardio-oncology in the future.
